A multi-view contrastive learning framework for spatial embeddings in risk modelling
Updated
Updated · arxiv.org · Aug 18
A multi-view contrastive learning framework for spatial embeddings in risk modelling
1 articles · Updated · arxiv.org · Aug 18
Summary
Researchers have introduced a multi-view contrastive learning framework for generating spatial embeddings to enhance risk modelling in insurance and real estate.
The model combines satellite imagery and OpenStreetMap data, enabling the creation of rich spatial features from coordinates alone, improving predictive accuracy in various models.
This approach allows for better generalisation to new regions and supports explainable spatial effects, offering practical benefits for actuaries and risk analysts.